FutureWarning of DatetimeProperties.to_pydatetime is depircated for plot_plotly and m.plot()

[RoshanAli339]

The m.plot(forecast) or the plot_plotly(m, forecast) functions when executed result in a FutureError the reads as follows

\Lib\site-packages\prophet\plot.py:71: FutureWarning: The behavior of DatetimeProperties.to_pydatetime is deprecated, in a future version this will return a Series containing python datetime objects instead of an ndarray. To retain the old behavior, call np.array on the result
fcst_t = fcst['ds'].dt.to_pydatetime()

venv\Lib\site-packages\prophet\plot.py:72: FutureWarning: The behavior of DatetimeProperties.to_pydatetime is deprecated, in a future version this will return a Series containing python datetime objects instead of an ndarray. To retain the old behavior, call np.array on the result
ax.plot(m.history['ds'].dt.to_pydatetime(), m.history['y'], 'k.',

If there is any way to get through this, please help me or please make necessary changes to resolve this error.

[suhaanibatra]

Facing the same issue, even if I haven't used the to_pydatetime function.

[kmezhoud]

Here a prophet example that returns this error message.

/home/.local/lib/python3.10/site-packages/prophet/plot.py:72: FutureWarning: The behavior of DatetimeProperties.to_pydatetime is deprecated, in a future version this will return a Series containing python datetime objects instead of an ndarray. To retain the old behavior, call `np.array` on the result
  fcst_t = fcst['ds'].dt.to_pydatetime()
/home/.local/lib/python3.10/site-packages/prophet/plot.py:73: FutureWarning: The behavior of DatetimeProperties.to_pydatetime is deprecated, in a future version this will return a Series containing python datetime objects instead of an ndarray. To retain the old behavior, call `np.array` on the result
  ax.plot(m.history['ds'].dt.to_pydatetime(), m.history['y'], 'k.',

df = pd.read_csv('https://raw.githubusercontent.com/facebook/prophet/main/examples/example_wp_log_peyton_manning.csv')

# Python
m = Prophet()
m.fit(df)
future = m.make_future_dataframe(periods=365)
forecast = m.predict(future)
fig1 = m.plot(forecast)

[kmezhoud]

You can reproduce the plot with something like this.

plt.scatter(fcast['ds'], fcast['yhat'], color='black', alpha=0.5, s =1)

# Plot the confidence intervals
plt.fill_between(fcast['ds'], 
                            fcast['yhat_lower'],
                             fcast['yhat_upper'],
                               color='blue',
                                alpha=0.05) #, label='Confidence Interval'

# Add labels and legend
plt.xlabel('Date')
plt.ylabel('Value')
#plt.legend()
# Show the plot
plt.show()

[datager]

Facing this issue same:

import pandas as pd
from prophet import Prophet
df = pd.read_csv('example_wp_log_peyton_manning.csv') # https://raw.githubusercontent.com/facebook/prophet/main/examples/example_wp_log_peyton_manning.csv'
# df = pd.read_csv('a.csv')
# h = df.head()
# print(h)

m = Prophet()
m.fit(df)

future = m.make_future_dataframe(periods=365)
t = future.tail()
print(t)

forecast = m.predict(future)
r = forecast[['ds', 'yhat', 'yhat_lower', 'yhat_upper']].tail()
print(r)
fig1 = m.plot(forecast)
# fig2 = m.plot_components(forecast)
fig1.show()
# fig2.show()

/opt/homebrew/lib/python3.11/site-packages/prophet/plot.py:72: FutureWarning: The behavior of DatetimeProperties.to_pydatetime is deprecated, in a future version this will return a Series containing python datetime objects instead of an ndarray. To retain the old behavior, call `np.array` on the result
  fcst_t = fcst['ds'].dt.to_pydatetime()
/opt/homebrew/lib/python3.11/site-packages/prophet/plot.py:73: FutureWarning: The behavior of DatetimeProperties.to_pydatetime is deprecated, in a future version this will return a Series containing python datetime objects instead of an ndarray. To retain the old behavior, call `np.array` on the result
  ax.plot(m.history['ds'].dt.to_pydatetime(), m.history['y'], 'k.',